We had interesting panel discussion on the topic Innovations driving next generation enterprise

Trends

* Now, the personal computing is more affordable compare to 1960s and 1980s due to to reduction is computing cost, storage cose and emergence of open source culture.

* In 1990s all the computers are interconnected and the Internet emerged along with new business models for finance/banking, retail e-commerce and e-mail. New enterprises also got emerged. Today we are living in digital age or mobile age.

* The people who born around 1995, have entered as work force around 2015. Generation Z, how to influence these 2 billion people, with different set of expectations.

* IoT

* Emergence of rural area. Now rural people also have access to information.

* Now people feel pride to work at startups.

* A new startup can be started just using WhatsApp groups.

* Supportive governments and Law. Few examples of few funny laws, that exist even today. Laws are reaction to 150 years of industrial revolution. The government should not stop the growth. So Karnatak is first state in India with regulatory sandbox, where you are allowed to break (only state) law for duration ranges from 3 months to 2 years, powered by Karnataka Innovation Authority. More can be achieve on startup front with de-regularization like allowing crypto currency.

* All the new innovations are becoming necessities.

* Big giant companies like IBM are supporting startups by finance, by connecting them to large customer base, scaling up. They cannot continue with their own R&D center so they come to startups. Block chain based virtual idea market may emerged in next few months.

* Online transactions will ultimately eliminate the need for banks.

* Education: 500 Mbps bandwidth at each home, will eliminate universities. all students will study online. Then even 6th standard students will talk about Artificial Intelligence, Machine Learning, IoT, Block Chain etc.

* The rule based and law based audit will change. Already after GST and demonetization the B.Com degree has more value compare to BBA or BBM. Now working people need to play different roles to remain in job market. Innovations at large enterprises are reducing jobs. On the other hand, same innovation increases the jobs at startups.

The factors that drives innovations are changed based on above trends. The generation z is consumer as well as is at startups, so disruption is bound to happen. Now all enterprise needs innovation to survive or to make more profit in areas of their products, service and/or process.

Discovery v/s Invention v/s Innovation

We know discovery is about something that already exists. Invention is one step further, by combining multiple few discoveries. Innovation goes even further by combining multiple inventions and build a use case to satisfy needs. The startups are all about building faster, better, cheaper solutions with help of inventions. Today major innovations are around (1) Artificial Intelligence, (2) data science and (3) block chain. Again startups need to focus on usage rather than the technology. 90% of startups fail due to lecuna about how to take it forward. All entrepreneurs cannot scale up their venture. Startups are risky, but design driven approach, reduces the risk.

It is not important, what you study (in college/school to get your degree). The important aspect is what you continue to study. Today everyone should know, how to learn new topics, unlearn old topics and re-learn as per emerging trends.

There was an interesting experiment on a patient, who daily forgets her past life. Everyday, she introduce herself, shake hands like meeting for the first time. The scientist doctor, started hurting her with small pin, during shake hand. Just in few days, she stopped shake hands with the scientist, even though she could not recover any memory associated about him. There are many research on topics of fear, fact, emotions, memory etc. Brain Research in the age of information technologyAs per Moravec's paradox, what we human beings find very easy is difficult for computers and what is easy for computers, that we find the most difficult. Like computer compare two images, pixel by pixel and so it cannot identify two objects are same, if the images are from different angle. On other way, two images of up-side-down faces, we human beings find identical, but when we rotate 180 degree, we realize they are different. It is easy for computer to tell, that they are different, as it compare pixel by pixel. Today 80 % of object detection is done by AI/ML.The 40% of our brain are is involved in visual processing. The brains does not look at brightness of pixel. We also discussed about famous image, about a dress, where a group people says white and blue, while others say gold and black. The color depends on individual perception about color of light falling on that dress white or yellow. Symmetry in deep learning network, increases accuracy from 1 to 10 %. Few initiatives: * OpenAI is a non-profit AI research company, discovering and enacting the path to safe artificial general intelligence. Many projects by OpenAI on github. * VisionLab@IISc, Bangalore. Website and Facebook pageAshwini Godbole emphasize on trans-disciplinary approach of brain health as per Ayurveda and modern biomedicine for brain. She also explained about clinic to lab approach. She mentioend about meaningful eating.

DIKSHAA means initiation. One can not grasp the spiritual knowledge using intelligence. The God, or the consciousness or the BHRAMAN is beyond intelligence. It cannot be proved or disproved with arguments. The Guru make us enter into this realm, that is beyond intelligence by means of DIKSHAA. It is a traditional ceremony, rituals, where Guru gives a secret and sacred MANTRA to the disciple.Today let me share an old photograph of my DIKSHA Guru, who initiate me with BHRAM-SAMBANDH may be around year 1993.

Damiel Manuel talked about Cyber Security. In this world, millions and billions of people are active on various social media like Facebook, WhatsApp, Instagram, YouTube, LinkedIn etc. It rises "deep fake" video threat. The video footage that appears to be real but is produced by technology. Now, we can no longer believe our eyes. NIST is a cyber security framework. Link 1 and Link 2 Cyber security is also a layered architecture. Hardware and network security is at physical layer. Application/software security at logical layer. Data security includes protection of personal information, location, accessibility, integrity of data etc. Social aspects covers people, culture and processes. it needs more attention. Cyber security topic now moves to Cyber resilienceInteresting panel discussions about AI/ML. Ajay Sharma : Machine used to crunch numbers and humans make decision. Now machines are capable of doing both. Use cases (1) use Intel Mobileye to prevent, predict accident zones. (2) CheXNeXt is deep learning for chest radiograph diagnosis. Discussion about Niti Ayog #AIforAll ICTAI (International Center for Transformative AI) etc. Raj Cherubal: Smart City solutions : (1) Parking management system (2) public bicycle sharing (3) restoration of water bodies (ponds) (4) solar panel on government buildings (5) water meter (6) smart class (7) disaster management system etc. IUDX (Indian Urben Data Exchange)Link Whitepaper Link

Aksah Ravi (gnani) talked about NLP based voice assistant products that supports Hindi, Kannada etc. Out of all AI/ML projects hardly 13 to 14 % projects are successful and only 8% of customer are happy. Some projects need their ML model to be updated every week, even every day. AI/ML business case is all about identifying and satisfying unmet and unmentioned need. Few challenges (1) AI/ML implementation needs cultural change, where man and machine both work together. (2) upskill of existing staff (3) Data is fuel for AI. More time goes to find out which data to use rather than building AI/ML model. Noise in data can cause bias.The chatbot may learn offensive language over time. (4) explain-ability of AI/ML outcome. (5) Robust governance is also important. At present, chatbots are becoming popular. Long way to go. Information architecture (IA) is must for AI/ML projects. IA is the structural design of shared information environments.

Queryplexand federationare effective tools from IBM to connect multiple data sources. AI OpenScale is another tool from IBMAshok Ayengar talked about shopx - buy and sale platform. Last 25 years of history big enterprise adopted new technologies like ERP and small stratup companies built eco-system around it. Many fortune 500 companies have huge legacy in range of 20 to 100 years. They need machine learning even on end-of-life servers. The collaboration at Bangalore is not seen even in developed country. Here we have hackathon, open source contribution, discussion at physical meetup etc. It is really proud to be in Bangalore. The day 1 ended with thought leaders conclave on "TechScape 2035"The following trends are emerged. 1. Digitalization2. Rapid Urbanization3. Customer does not want product, but wants solution4. so more and more collaborations

The growth of Internet was not predicated. 1. Growth with many IoT devices2. Growth for amusement e.g. Netflix3. Many networks E.g. Car has many networksDuring 90s, when Internet based innovative services and business was planned, no one predicated that everyone (4 billion people) will have smart phone. Now cost of computing come down. Technology is democratized. This growth will be accelerated further, as everything (e.g. speaker, light etc.) will have compute power, connectivity, intelligent (AI/ML). The enormous data is generated by our wearable. Evolution will happen in laboratory and new human being will be created. Excitement with fear. Now the smart software makes diagnosis smarter than doctor. In next 5 to 10 years, it will be mandatory to take second opinion from machines. People will get incentive for not being sick by health insurance and hospitals. The Indian doctors and nurses are best in the world. This is a license driven industry. Now in automobile people need : 0 emission, 0 downtime, 0 accident, and first solution is electric car. Electricity is alternate fuel. The omnipresent 3D printing will eliminate need to keep inventory of spare parts of cars. The digitization, GST have improved logistics a lot. We need more efficiency steps like: spare trailers will just replace the loaded one to save time. All these trends will empower the bottom of pyramid, surprisingly. In future, there is no concept of firm. All companies are becoming platform. Apple started as platform for iOS apps. People starts company just on WhatsApp group. Now we will see rapid consolidation of firms. So monopoly will be back. The present generation is Digital Native and generation ZTheir working style is completely different.

CDelivery = CI + deploy at production like environment (staging) + automate integration testing + automate acceptance testing + smoke testingPrinciples2.2.1 Build artifact once2.2.2 Artifact should be immutable2.2.3 Deployment to production like environment = load balancers + n/w settings + security controls + data that matches production2.2.4 stop if previous step fails2.2.5 Deployment should be idempotent CDeployment = CDelivery + Full automated testing + Deployed to production For higher performances teams* Less than 3 branch (ideally 1 branch)* Their life span is less than a day and then merge to trunk. It is not about how much you can deliver but it is about how little you canCDelivery the build is not always release to production environment. CDeployment, the build is always release to production environment.

Define your infrastructure as model or drive it using RESTful APIModel OR Recipes = Hardware + OS(Operating System) + OS Dependencies + System Configuration + Accounts + SSL Certs + ApplicationImportant terms* Imperative (procedural) Approach where commands desired to produce a state are defined and then executed. E.g. BASH Shell script, AWS CLI, Python Boto library * declarative (functional) Approach where you define the desired state, and the tool converges the existing system on the model. E.g. Makefile, Puppet manifest, SQL Queries.declarative is more efficient.* Convergent : CM automation that converges the system to desired state. * Idempotent : The ability to execute the CM procedure repeatedly. And end up in the same state each time. The second run will not make any change. * Immutable : Not change after deployment. Can be redeploy if needed. E.g. Docker container. * Self service : The ability for an end user to kick off one of these processes without having to go through other people

PyCharm is an IDE for Python development. Here are few key take away points:

$ pip freeze > requirements.txt

This will create a requirements.txt file, which contains a simple list of all the packages in the current environment, and their respective versions. Later, when a different developer (or you, if you need to re- create the environment) can install the same packages, with the same versions by running

Pipenv is a tool that provides all necessary means to create a virtual environment for your Python project. It automatically manages project packages through the Pipfile file as you install or uninstall packages.

Yantra (यन्त्र) (Sanskrit) (literally "machine, contraption" is a mystical diagram, mainly from the Tantric traditions of the Indian religions.

They are used for the worship of deities in temples or at home; as an aid in meditation; used for the benefits given by their supposed occult powers based on Hindu astrology and tantric texts. They are also used for adornment of temple floors, due mainly to their aesthetic and symmetric qualities. Specific yantras are traditionally associated with specific deities.

Yantras are usually associated with a particular deity and are used for specific benefits, such as: for meditation; protection from harmful influences; development of particular powers; attraction of wealth or success, etc.They are often used in daily ritual worship at home or in temples, and sometimes worn as a talisman.

As an aid to meditation, yantras represent the deity that is the object of meditation. These yantras emanate from the central point, the bindu. The yantra typically has several geometric shapes radiating concentrically from the center, including triangles, circles, hexagons, octagons, and symbolic lotus petals. The outside often includes a square representing the four cardinal directions, with doors to each of them

Yantras can be on a flat surface or three dimensional. Yantras can be drawn or painted on paper, engraved on metal, or any flat surface. They tend to be smaller in size than the similar mandala, and traditionally use less color than mandalas.

Occult yantras are used as good luck charms, to ward off evil, as preventative medicine, in exorcism, etc., by using their magical power. When used as a talisman, the yantra is seen to represent a deity who can be called on at will by the user. They are traditionally consecrated and energized by a priest, including the use of mantras which are closely associated to the specific deity and yantra. Practitioners believe that a yantra that is not energized with mantra is lifeless

A yantra comprises geometric shapes, images, and written mantra. Triangles and hexagrams are common, as are circles and lotuses of 4 to 1,000 petals.